Abstract
High-throughput pooled resequencing offers significant potential for whole
genome population sequencing. However, its main drawback is the loss of
haplotype information. In order to regain some of this information, we present
LDx, a computational tool for estimating linkage disequilibrium (LD) from
pooled resequencing data. LDx uses an approximate maximum likelihood approach
to estimate LD (r2) between pairs of SNPs that can be observed within and among
single reads. LDx also reports r2 estimates derived solely from observed
genotype counts. We demonstrate that the LDx estimates are highly correlated
with r2 estimated from individually resequenced strains. We discuss the
performance of LDx using more stringent quality conditions and infer via
simulation the degree to which performance can improve based on read depth.
Finally we demonstrate two possible uses of LDx with real and simulated pooled
resequencing data. First, we use LDx to infer genomewide patterns of decay of
LD with physical distance in D. melanogaster population resequencing data.
Second, we demonstrate that r2 estimates from LDx are capable of distinguishing
alternative demographic models representing plausible demographic histories of
D. melanogaster.
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